PI: Richard D. Lange

I am an assistant professor in the Department of Computer Science at RIT, with additional appointments in the Cognitive Science PhD Program and the Center for Vision Science.

I want to understand how the brain works and use that understanding to create more capable machine learning and AI systems. My interests have bounced back and forth over the years between computer science, neuroscience, AI, machine learning, and philosophy of mind.

Here's a bit about how I got where I am now:

2013: BA in Computer Science and Engineering at Dartmouth College. Near the end of undergrad I fell in love with the idea of building intelligent systems inspired by how the brain works.
2014-2015: Started a PhD in Computer Science at the University of Rochester. Eventually realized that building "brain inspired" AI means we first need to understand brains.
2015-2020: PhD in Brain and Cognitive Science at the University of Rochester in the lab of Ralf Haefner. Studied visual perception both in theory and in humans and monkeys through the lens of Bayesian inference.
2020-2023: Postdoc at the University of Pennsylvania in Konrad Kording's lab. Studied deep neural networks and structure in the kinds of internal representations they develop.
2023 Started as Assistant Professor of Computer Science at RIT

New and ongoing research areas – get in touch if you're interested in any of the following!

Improved self-supervised representation learning with uncertainty quantification*
Improved measures of representational similarity for neural data*
Improved general-purpose black-box statistical inference*
Information processing with stochastic neural networks*
Improved mathematical frameworks for uncertainty quantification and information-processing
Causal world-models and counterfactual learning

* Some opportunities for MS and UG students to get involved in these areas

How to get involved

Current RIT MS or UG students

Reach out to talk about possible thesis or capstone projects. It's common and encouraged to do an independent study first so you can spend 1 semester learning background material and 1 semester doing your project.

Reach out early! My schedule fills up quickly.

Paid RA positions are not currently available, but might be in the future, pending funding.

Not currently recruiting new PhD students

Past research highlights

Click here for Google Scholar

Understanding neural representations

Vision as Bayesian inference

Improving inference algorithms

Inference dynamics during decision-making